Scientific Program

Below you can find the sessions that will be held during the conference. All of which cover exciting and novel developments in the field.

We will touch on machine learning, precision medicine, and even hold a workshop on AWS Sagemaker. Click through to learn more!


Select an event to see speaker information

DAY 1: March 15th, 2023

  • 11:00am - 6:30pm Check-in, Registration, and Posters

  • 1:00pm - 1:10pm Meet and Greet

  • 1:10pm - 1:20pm Opening and Welcome Remarks

    Dr Inimary Toby

  • 1:20pm - 2:15pm Keynote Address

    Dr Ruth Roberts

  • 2:15pm - 2:30pm Break

  • 2:30pm - 3:45pm YSEA Session for Post-doctoral Fellows

  • 3:45pm - 4:00pm Break

  • 4:00pm - 5:15pm YSEA Session for Students

  • 5:15pm - 06:45pm Poster Session

    Students and Post-Doctoral Fellows. Light refreshments provided

  • 7pm Shuttle Service

    Toyota Music Factory for dinner options

DAY 2: March 16th, 2023

  • 8:00am - 4:00pm Onsite Registration Opens

  • 8:30am - 9:30am Keynote Speaker

    Dr Kurt Zimmerman

  • 9:30am - 9:40am Break

  • 9:40am - 10:50am Breakout Sessions I and II

    ML and Deep Learning in Precision Medicine and Drug Safety Evaluation

  • 10:50am - 11:00am Break

  • 11:00am - 12:20pm Breakout Sessions III and IV

    Immuno-Oncology and Single Cell Multi-omics

  • 12:20pm - 1:30pm Lunch and MCBIOS Business Meeting

  • 1:30pm - 3:30pm Workshop I

    AWS SageMaker Immersion Day Workshop

  • 2:30pm - 3:30pm Breakout Session V

    The Business of Scientific

  • 3:30pm - 3:45pm Break

  • 3:30pm - 3:45pm - 4:15pm Plenary Speaker

    Dr Mikhail Dozmorov

  • 4:15pm - 4:20pm Break

  • 4:20pm - 5:45pm Workshop II

    Career Development for Trainees

  • 4:20pm - 5:45pm Workshop III

    NIBLSE Educational Resources

  • 6pm - Dinner (OYO)

DAY 3: March 17th, 2023

  • 7:30am - 8:50am Board members meeting

  • 9:00am - 9:50am Keynote Speaker

    Dr Isaac Chan

  • 9:50am - 10:00am Break

  • 10:00am - 11:20am Breakout Session VI and VII

    Network medicine and Drug Discovery and Emerging tools for “omics” studies

  • 11:30am - 12:15pm Keynote Address

  • 12:15pm - 1:30 pm Lunch, Awards banquet and Closing

Dr. Ruth Roberts

Ruth A. Roberts, PhD

Professor Ruth A. Roberts is Chair and Director of Drug Discovery at Birmingham University, UK and Cofounder of ApconiX, recent winners of the 2022 Queen's award for Enterprise in Exports. Previously, Ruth was Global Head of Regulatory Safety at AstraZeneca (2004-2014), Director of Toxicology for Aventis in Paris, France (2002-2004) and Head of Cancer Biology at Central Toxicology Laboratory (1990-2002).

Dr. Kurt Zimmerman

Kurt Zimmerman, PhD

Doctor Zimmerman is an assistant professor at the University of Oklahoma Health Sciences Center who focuses on understanding the role of immune cells in polycystic kidney and liver disease(PKD). The goal of this research is to develop new approaches and targets for treatment of patients suffering from PKD.

Dr. Kurt Zimmerman

Isaac Chan, MD, PhD

Isaac Chan, M.D. Ph.D., is an Assistant Professor in the Department of Internal Medicine at UT Southwestern Medical Center and a member of its Division of Hematology Oncology. He specializes in immunotherapy, breast cancer, and metastatic cancer.

During his MD/PhD training at University of North Carolina and medical oncology fellowship at Johns Hopkins University.

Dr. Ruth Roberts

Mikhail Dozmorov, PhD

Dr. Mikhail Dozmorov is an associate professor in the Biostatistics department, Virginia Commonwealth University. He develops statistical methods and bioinformatics tools for the integrative analysis of genomics datasets.

Through collaborations with basic and clinical cancer researchers, he analyzed and interpret RNA-seq, ChIP-seq, DNA methylation, single-cell sequencing data. He is developing biostatistical methods and software to analyze the three-dimensional structure of the genome obtained with Chromatin Conformation Capture sequencing technologies (e.g., Hi-C).

Precision Medicine advocates for the practice of customized disease treatment and prevention such that all clinical decisions are made based on the characteristics of individual patients.

During this session we'll showcase the latest research developments in the areas of applying advanced Artificial Intelligence and Machine Learning and Big Data informatics in precision medicine.

Machine learning have been widely applied in almost every field such as science and medicine.

Advancements in machine learning and deep learning are paving the road to future data science and will have significant impacts on the public health. This session is intended for experts and students in this field to exchange their experiences and achievements and explore potential collaborations.
The fundamental questions for the integrative multi-omics network-based analysis are "How can we remove noise and boost signals from multi-omics data analytics?", "How can we screen biological conditional interactions and regulations using multi-omics data?", "How can we further improve the odds of precision medicine's success using the multi-omics data?".

This session aims to trigger the common interest in the MCBIOS community for rethinking and revisiting the crucial questions in utilizing multi-omics data for personalized medicine and coupling network biology with cutting-edge multi-omics technologies.
Single-cell analysis has revolutionized biomedical sciences by becoming a converging technology for modern genetics, cell biology, immunology, biochemistry, and disease biology studies.

Coupling with AI/ML, single-cell multi-omics studies may provide insights on how organs evolve and how a disease progresses. In this session, we will solicit late-breaking primary research in the follwing topics and more during a 2-hr session:
  • How can we impute data and reduce data noises from different single-cell analytical assays?
  • How can we balance knowledge-guided and knowledge-agnostic approaches in characterizing cell types and their relationships based on embedding clusters?
  • How can we infer intercellular and intracellular signaling network data at the molecular and cellular level?
Despite the significant improvements in the treatment of cancer with new treatment agents like advanced and adjuvant disease settings of solid tumors and hematologic malignancies, many patients still do not achieve long-term disease remission and control.

New computational methods are needed to extract, integrate and interpret these high-dimensional data sets to develop effective biomarkers for immunotherapies. This session will focus on new and innovative computational methods in immuno-oncology.
Amazon SageMaker is a fully managed machine learning service. With SageMaker, data scientists and developers can quickly and easily build and train machine learning models, and then directly deploy them into a production-ready hosted environment.

The only pre-requisite to participate the hands-on workshop is a laptop with internet access.